DOI: 10.3724/SP.J.1249.2012.04341

Journal of Shenzhen University Science and Engineering (深圳大学学报理工版) 2012/29:4 PP.341-346

Recognition algorithm of white foreign fibers in cotton based on gray level co occurrence matrix

The recognition of white foreign fibers in lint has always been a difficulty in cotton detection. Because the gray values of white foreign fibers are approximate to lint, it is very difficult to recognize white foreign fibers just by gray value. Through the texture feature analysis of lint and white foreign fibers, it was found that the entropy of gray level co occurrence matrix (GLCM) could be used to judge whether there were white foreign fibers in lint. According to the gray value characteristics of lint and white foreign fibers, this paper compressed the gray level piecewise and nonuniformly. Thus, the threshold segmentation method based on texture features was put forward, and white foreign fibers were recognized from lint by means of the entropy threshold segmentation method. Results showed that compressing the gray level piecewise and non-uniformly could effectively reduce the computing time and guarantee the accuracy of recognition at the same time, and this algorithm can effectively improve the speed and precision of white foreign fibers recognition.

Key words:foreign fibers,cotton,image segmentation,texture,gray level co occurrence matrix,entropy

ReleaseDate:2014-07-21 16:19:12

Funds:Science and Technology Supporting Xinjiang Special Plan(2011AB017); “Quancheng Scholars”Construction Projects of Jinan(201109)

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